IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/29900.html
   My bibliography  Save this paper

Reporting Heterogeneity in Self-Assessed Health among Elderly Europeans: The Impact of Mental and Physical Health Status

Author

Listed:
  • Pfarr, Christian
  • Schmid, Andreas
  • Schneider, Udo

Abstract

Self-assessed health (SAH) is a frequently used measure of individuals’ health status. It is also prone to reporting heterogeneity. To control for reporting heterogeneity valid measures of the objective health status are needed. The topic becomes even more complex for cross-country comparisons, as many key variables tend to vary strongly across countries, influenced by cultural and institutional differences. This study aims at exploring the key drivers for reporting heterogeneity in SAH in an international context. To this end, country specific effects are accounted for and the objective health measure is concretized, separating out effects of mental and physical health conditions. We use panel data from the Survey of Health, Ageing and Retirement in Europe (SHARE) which provides a rich dataset on the elderly European population. To obtain distinct indicators for physical and mental health conditions two indices were constructed. Finally, to identify potential reporting heterogeneity in SAH a generalized ordered probit model is estimated. We find evidence that health behaviour as well as health care utilization, mental and physical health condition as well as country characteristics affect reporting behaviour. We conclude that observed and unobserved heterogeneity play an important role when analysing SAH and have to be taken into account.

Suggested Citation

  • Pfarr, Christian & Schmid, Andreas & Schneider, Udo, 2011. "Reporting Heterogeneity in Self-Assessed Health among Elderly Europeans: The Impact of Mental and Physical Health Status," MPRA Paper 29900, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:29900
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/29900/1/MPRA_paper_29900.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Butler, J S, 1987. "Measurement Error in Self-reported Health Variables," The Review of Economics and Statistics, MIT Press, vol. 69(4), pages 644-650, November.
    2. Fabrice Etilé & Carine Milcent, 2006. "Income-related reporting heterogeneity in self-assessed health: evidence from France," Health Economics, John Wiley & Sons, Ltd., vol. 15(9), pages 965-981.
    3. repec:cup:apsrev:v:98:y:2004:i:01:p:191-207_00 is not listed on IDEAS
    4. Cristina Hernandez-Quevedo & Andrew M Jones & Nigel Rice, "undated". "Reporting Bias and Heterogeneity in Self-Assessed Health. Evidence from the British Household Panel Survey," Discussion Papers 04/18, Department of Economics, University of York.
    5. Marcel Kerkhofs & Maarten Lindeboom, 1995. "Subjective health measures and state dependent reporting errors," Health Economics, John Wiley & Sons, Ltd., vol. 4(3), pages 221-235, May.
    6. Teresa Bago d'Uva & Eddy Van Doorslaer & Maarten Lindeboom & Owen O'Donnell, 2008. "Does reporting heterogeneity bias the measurement of health disparities?," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 351-375, March.
    7. Nicolas R. Ziebarth, 2009. "Measurement of Health, the Sensitivity of the Concentration Index, and Reporting Heterogeneity," SOEPpapers on Multidisciplinary Panel Data Research 211, DIW Berlin, The German Socio-Economic Panel (SOEP).
    8. repec:hal:psewpa:halshs-00590524 is not listed on IDEAS
    9. Christian Pfarr & Andreas Schmid & Udo Schneider, 2011. "Estimating ordered categorical variables using panel data: a generalized ordered probit model with an autofit procedure," Journal of Economics and Econometrics, Economics and Econometrics Society, vol. 54(1), pages 7-23.
    10. Hendrik Jürges, 2007. "True health vs response styles: exploring cross‐country differences in self‐reported health," Health Economics, John Wiley & Sons, Ltd., vol. 16(2), pages 163-178, February.
    11. Lindeboom, Maarten & van Doorslaer, Eddy, 2004. "Cut-point shift and index shift in self-reported health," Journal of Health Economics, Elsevier, vol. 23(6), pages 1083-1099, November.
    12. Coe, Norma B. & Zamarro, Gema, 2011. "Retirement effects on health in Europe," Journal of Health Economics, Elsevier, vol. 30(1), pages 77-86, January.
    13. Greene,William H. & Hensher,David A., 2010. "Modeling Ordered Choices," Cambridge Books, Cambridge University Press, number 9780521194204, January.
    14. Maarten Lindeboom & Marcel Kerkhofs, 2009. "Health and work of the elderly: subjective health measures, reporting errors and endogeneity in the relationship between health and work," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(6), pages 1024-1046.
    15. John Bound, 1991. "Self-Reported Versus Objective Measures of Health in Retirement Models," Journal of Human Resources, University of Wisconsin Press, vol. 26(1), pages 106-138.
    16. Disney, Richard & Emmerson, Carl & Wakefield, Matthew, 2006. "Ill health and retirement in Britain: A panel data-based analysis," Journal of Health Economics, Elsevier, vol. 25(4), pages 621-649, July.
    17. repec:hal:wpaper:halshs-00590524 is not listed on IDEAS
    18. Ziebarth, Nicolas, 2010. "Measurement of health, health inequality, and reporting heterogeneity," Social Science & Medicine, Elsevier, vol. 71(1), pages 116-124, July.
    19. Teresa Bago d'Uva & Maarten Lindeboom & Owen O'Donnell & Eddy van Doorslaer, 2011. "Education‐related inequity in healthcare with heterogeneous reporting of health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(3), pages 639-664, July.
    20. Udo Schneider & Christian Pfarr & Brit Schneider & Volker Ulrich, 2012. "I feel good! Gender differences and reporting heterogeneity in self-assessed health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(3), pages 251-265, June.
    21. Richard Williams, 2006. "Generalized ordered logit/partial proportional odds models for ordinal dependent variables," Stata Journal, StataCorp LP, vol. 6(1), pages 58-82, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mayu Fujii & Takashi Oshio & Satoshi Shimizutani, 2014. "Self-rated Health Status of Japanese and Europeans in Later Life: Evidence from JSTAR and SHARE," The Japanese Economic Review, Japanese Economic Association, vol. 65(4), pages 483-498, December.
    2. Nádia Simões & Nuno Crespo & Sandrina B. Moreira & Celeste A. Varum, 2016. "Measurement and determinants of health poverty and richness: evidence from Portugal," Empirical Economics, Springer, vol. 50(4), pages 1331-1358, June.
    3. Andrew M. Jones; Nigel Rice, Silvana Robone; & Nigel Rice; & Silvana Robone:, 2012. "A comparison of parametric and non-parametric adjustments using vignettes for self-reported data," Health, Econometrics and Data Group (HEDG) Working Papers 12/10, HEDG, c/o Department of Economics, University of York.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Udo Schneider & Christian Pfarr & Brit Schneider & Volker Ulrich, 2012. "I feel good! Gender differences and reporting heterogeneity in self-assessed health," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(3), pages 251-265, June.
    2. Gimenez-Nadal, J. Ignacio & Molina, Jose Alberto, 2015. "Health status and the allocation of time: Cross-country evidence from Europe," Economic Modelling, Elsevier, vol. 46(C), pages 188-203.
    3. Valerii Baidin & Christopher J. Gerry & Maria Kaneva, 2021. "How Self-Rated is Self-Rated Health? Exploring the Role of Individual and Institutional Factors in Reporting Heterogeneity in Russia," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 155(2), pages 675-696, June.
    4. Kaneva, Maria & Baidin, Valerii, 2018. "Heterogeneity in reporting self-assessed health of the Russians," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 51, pages 102-125.
    5. Sarah Brown & Jennifer Roberts & Karl Taylor, 2010. "Reservation wages, labour market participation and health," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(3), pages 501-529, July.
    6. Davillas, Apostolos & de Oliveira, Victor Hugo & Jones, Andrew M., 2023. "Is inconsistent reporting of self-assessed health persistent and systematic? Evidence from the UKHLS," Economics & Human Biology, Elsevier, vol. 49(C).
    7. Teresa Bago d'Uva & Eddy Van Doorslaer & Maarten Lindeboom & Owen O'Donnell, 2008. "Does reporting heterogeneity bias the measurement of health disparities?," Health Economics, John Wiley & Sons, Ltd., vol. 17(3), pages 351-375, March.
    8. García-Gómez, Pilar & Jones, Andrew M. & Rice, Nigel, 2010. "Health effects on labour market exits and entries," Labour Economics, Elsevier, vol. 17(1), pages 62-76, January.
    9. Johnston, David W. & Propper, Carol & Shields, Michael A., 2009. "Comparing subjective and objective measures of health: Evidence from hypertension for the income/health gradient," Journal of Health Economics, Elsevier, vol. 28(3), pages 540-552, May.
    10. Juergen Jung, 2022. "Estimating transition probabilities between health states using US longitudinal survey data," Empirical Economics, Springer, vol. 63(2), pages 901-943, August.
    11. Laura Rossouw & Teresa Bago d’Uva & Eddy Doorslaer, 2018. "Poor Health Reporting? Using Anchoring Vignettes to Uncover Health Disparities by Wealth and Race," Demography, Springer;Population Association of America (PAA), vol. 55(5), pages 1935-1956, October.
    12. William H. Greene & Mark N. Harris & Bruce Hollingsworth, 2015. "Inflated Responses in Measures of Self-Assessed Health," American Journal of Health Economics, MIT Press, vol. 1(4), pages 461-493, Fall.
    13. Costa-Font, Joan & Hernández-Quevedo, Cristina, 2012. "Measuring inequalities in health: What do we know? What do we need to know?," Health Policy, Elsevier, vol. 106(2), pages 195-206.
    14. Black, Nicole & Johnston, David W. & Shields, Michael A. & Suziedelyte, Agne, 2017. "Who provides inconsistent reports of their health status? The importance of age, cognitive ability and socioeconomic status," Social Science & Medicine, Elsevier, vol. 191(C), pages 9-18.
    15. J. Ignacio Gimenez-Nadal & Jose Alberto Molina, 2016. "Health inequality and the uses of time for workers in Europe: policy implications," IZA Journal of European Labor Studies, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 5(1), pages 1-18, December.
    16. Nesson, Erik T. & Robinson, Joshua J., 2019. "On the measurement of health and its effect on the measurement of health inequality," Economics & Human Biology, Elsevier, vol. 35(C), pages 207-221.
    17. Arni, Patrick & Dragone, Davide & Goette, Lorenz & Ziebarth, Nicolas R., 2021. "Biased health perceptions and risky health behaviors—Theory and evidence," Journal of Health Economics, Elsevier, vol. 76(C).
    18. Bonsang, Eric & Caroli, Eve & Garrouste, Clémentine, 2021. "Gender heterogeneity in self-reported hypertension," Economics & Human Biology, Elsevier, vol. 43(C).
    19. Jiayi Wen & Zixi Ye & Xuan Zhang, 2024. "A New Testing Method for Justification Bias Using High-Frequency Data of Health and Employment," Papers 2403.06368, arXiv.org.
    20. Harris, M.N. & Zhao, X. & Zucchelli, E., 2016. "The dynamics of health and labour market transitions at older ages: evidence from a multi-state model," Health, Econometrics and Data Group (HEDG) Working Papers 16/30, HEDG, c/o Department of Economics, University of York.

    More about this item

    Keywords

    reporting heterogeneity; SHARE; generalized ordered probit;
    All these keywords.

    JEL classification:

    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • I10 - Health, Education, and Welfare - - Health - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:29900. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.